CN102202142A - Burr detection device and burr detection method - Google Patents
Burr detection device and burr detection method Download PDFInfo
- Publication number
- CN102202142A CN102202142A CN201010133482XA CN201010133482A CN102202142A CN 102202142 A CN102202142 A CN 102202142A CN 201010133482X A CN201010133482X A CN 201010133482XA CN 201010133482 A CN201010133482 A CN 201010133482A CN 102202142 A CN102202142 A CN 102202142A
- Authority
- CN
- China
- Prior art keywords
- template image
- pixel
- image
- burr
- black
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 43
- 229910000831 Steel Inorganic materials 0.000 claims description 33
- 239000010959 steel Substances 0.000 claims description 33
- 238000000034 method Methods 0.000 claims description 7
- 230000004044 response Effects 0.000 claims description 4
- 239000011148 porous material Substances 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 3
- 241000872198 Serjania polyphylla Species 0.000 description 2
- ATJFFYVFTNAWJD-UHFFFAOYSA-N Tin Chemical compound [Sn] ATJFFYVFTNAWJD-UHFFFAOYSA-N 0.000 description 1
- 239000006071 cream Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000011179 visual inspection Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/94—Investigating contamination, e.g. dust
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/94—Investigating contamination, e.g. dust
- G01N2021/945—Liquid or solid deposits of macroscopic size on surfaces, e.g. drops, films, or clustered contaminants
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Image Analysis (AREA)
- Image Processing (AREA)
Abstract
The invention discloses a burr detection method, which comprises the following steps of: scanning an image in a preset target area according to preset scanning rules to obtain a template image corresponding to the preset scanning rules; judging whether a central pixel of the template image has a target value or not; if the central pixel of the template image is judged to have the target value, obtaining a number value of pixels, with the target value, corresponding to counting rules in each template image according to the counting rules; judging whether the number value of the pixels with the target value is greater than a preset reference value or not; and if the number value of the pixels with the target value is not greater than the preset reference value, determining an open pore corresponding to the template image has burrs, and outputting prompting information. The invention also provides a burr detection device.
Description
Technical field
The present invention relates to the product detection range, particularly a kind of burr detection device and burr detection method that detects burr in the steel plate perforate.
Background technology
Surface mounting technology (Surface Mounted Technology needs to use the steel plate with perforate in processing procedure SMT), with tin cream by perforate be printed on printed circuit board (PCB) (Printed Circuit Board, PCB) on.All need the situation of its upper surface hole is detected at the processing procedure of steel plate with in using, avoid because the burr in the hole or the existence of foreign matter, the printing that causes printed circuit board (PCB) is bad and the generation in man-hour is additionally reprocessed in increase, causes the increase of manufacturing cost.
The existing burr mode that detects in the steel plate perforate is mainly Manual Visual Inspection, yet generally the quantity of perforate has thousands ofly on every steel plate, so makes testing staff's workload strengthen, and is unfavorable for modernized pipelining.
Summary of the invention
Given this, be necessary to provide a kind of burr detection device that can detect burr in the steel plate perforate automatically.
Also be necessary to provide a kind of burr detection method that can detect burr in the steel plate perforate automatically.
A kind of burr detection device comprises: processing module and output module.Processing module is used for scanning in default target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule, and when the center pixel of judging template image is desired value, obtain in this template image and the corresponding quantitative value of statistical rules according to statistical rules with pixel of desired value, and judge that when the quantitative value of judging the pixel with desired value is not more than preset reference value the perforate corresponding with this template image has burr, and the output information is given output module.Output module is used for information is exported.
A kind of burr detection method, this method comprises the steps:
Scan in default target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule;
Whether the center pixel of judging template image is desired value;
When the center pixel of judging template image is desired value, obtain in each template image and the corresponding quantitative value of statistical rules with pixel of desired value according to statistical rules;
Whether the quantitative value of judging the pixel with desired value is not more than preset reference value;
When being not more than preset reference value, the quantitative value of judging the pixel with desired value judges that the perforate corresponding with this template image has burr, and the output information.
By above-mentioned burr detection device and burr detection method, processing module is according to scanning in target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule, and when the center pixel of judging template image is desired value, obtain in this template image and the corresponding quantitative value of statistical rules according to statistical rules with pixel of desired value, and judge that when the quantitative value of judging the pixel with desired value is not more than preset reference value the perforate corresponding with this template image has burr, and the output information is given output module.So, burr detection device does not need artificial participation just can finish burr detecting operation to perforate on the steel plate automatically, has reduced testing staff's workload, helps modernized pipelining.
Description of drawings
Fig. 1 is the functional block diagram of the burr detection device of a better embodiment.
Fig. 2 is the schematic diagram of template image.
Fig. 3 is for target area image and scan the schematic diagram of the template image that this target area image produces.
Fig. 4 is the functional block diagram of processing module shown in Figure 1.
Fig. 5 moves the functional block diagram that produces after the burr trace routine for central processing unit shown in Figure 4.
Fig. 6 is another functional block diagram of processing module shown in Figure 1.
Fig. 7 is the burr detection method flow chart of a better embodiment.
The main element symbol description:
Burr trace routine 300
Acquiring unit 302
First comparing unit 303
Second comparing unit 305
Template image 101,102,103,104
Field programmable gate array 400
Position generative circuit 401
Time-delay sample circuit 403
Burr detection method flow chart S600～S610
Embodiment
Please consult Fig. 1 simultaneously, burr detection device 20 comprises image collection module 21, processing module 22 and output module 23.
Coordinate and predeterminable area that image collection module 21 is used for describing according to being used for of filing in advance the steel plate position of opening obtain rule picked-up target area image.Wherein, target area image adopts one group two to advance value and represent, can be stored in the processing module 22.This is filed in advance and is used to describe the information of steel plate, for example size of perforate etc. on the coordinate of perforate correspondence and the steel plate on the quantity of perforate, the steel plate on the size of steel plate, the steel plate; This predeterminable area obtains rule for determine the size of target area image according to the size of the perforate on the steel plate.
Below illustrate the process that burr detection device 20 detects burr in the steel plate perforate, wherein template image is of a size of 5*5 pixel size, and fiducial value is 5, please be simultaneously referring to Fig. 3, image collection module 21 is obtained target area image 100, comprises a perforate in this target area image 700; Processing module 22 scans in target area image 700 to obtain template image 101 according to default scanning rule, 102,103,104, processing module 22 is respectively to template image 101,102,103,104 carry out the center pixel color judges, processing module 22 is judged template image 101,102, after 103 center pixel color is black, according to statistical rules difference statistical mask image 101,102, the quantitative value of the black picture element on 103 four limits, processing module 22 counts template image 101,102, the quantitative value of the black picture element on 103 four limits is respectively 16,10,2, processing module 22 is with quantitative value 16,10,2 compare with fiducial value 5 one by one, when processing module 22 compares quantitative value 2 less than fiducial value 5, processing module 22 judges that these target area image 100 pairing perforates have burr, then export information and give output module 23, so that output module 23 is shown to the testing staff with information.
See also Fig. 4, processing module 22 comprises central processing unit (Central Processing Unit, CPU) 220 and memory 222.This memory 222 is used for storage operating system program 500, burr trace routine 300, target area image.Move the central processing unit 220 of operating system program 500 and can control the perforate that image collection module 21 is taken on the steel plate.
Please be simultaneously referring to Fig. 5, this central processing unit 220 produces following functional unit in these burr trace routine 300 backs of operation:
Acquiring unit 302 is used for according to default scanning rule target area image being scanned, to obtain and the corresponding template image of default scanning rule.
First comparing unit 303 is used to judge whether the center pixel of template image is black, and when the center pixel of judging template image is black, produces first comparison signal, and sends first comparison signal to statistic unit 304.
Second comparing unit 305 is used to judge whether the black picture element quantitative value is not more than preset reference value, and produces second comparison signal when black picture element quantitative value is not more than preset reference value judging, and second comparison signal is offered output unit 306.
In another embodiment, processing module 22 comprise field programmable gate array 400 after memory 222, the programming (Field-Programmable Gate Array, FPGA).This memory 222 is used for the target area image that memory image acquisition module 21 is taken.Field programmable gate array 400 after this programming produces corresponding circuit to realize the burr measuring ability, please be simultaneously referring to Fig. 6, this field programmable gate array 400 comprises position generative circuit 401, data converting circuit 402, time-delay sample circuit 403, decision circuitry 404, computing circuit 405, comparison circuit 406 and output circuit 407:
Position generative circuit 401 is used for according to the coordinate generation corresponding address data that are used for describing the steel plate position of opening of filing in advance, and address date is offered memory 222;
Time-delay sample circuit 403 is used to receive binary data and the buffer memory that data converting circuit 402 provides, when the binary data of buffer memory reached the size of template image, time-delay sample circuit 403 offered buffer memory and the pairing binary data of center pixel template image decision circuitry 404 and the pairing binary data of pixel on buffer memory and four limits template image is offered computing circuit 405;
Quantitative value and preset reference value that comparison circuit 406 is used for receiving compare, and produce comparison signal when the quantitative value that compares reception is not more than preset reference value, and comparison signal is offered output circuit 407;
In addition, in other embodiments, burr detection device 20 comprises processing module 22 and output module 23.Processing module 22 obtains template image from the target area image scanning that prestores.The target area image that prestores is to describe the coordinate of steel plate position of opening and predeterminable area by other image acquiring devices according to being used in filing in advance to obtain rule and absorb.
As shown in Figure 7, it is the flow chart of the burr detection method of a better embodiment.This method is applied in the burr detection device, so that the burr that burr detection device can be finished perforate on the steel plate detects, this method comprises the steps:
Step S602, coordinate and the predeterminable area of describing the steel plate position of opening according to being used in filing in advance obtain rule picked-up target area image.Target area image can adopt one group two to advance value and represent, and is stored in the memory of burr detection device.This is filed in advance and is used to describe the information of steel plate, and this information comprises coordinate of perforate correspondence on the size of perforate on the quantity, steel plate of perforate on the size, steel plate of steel plate and the steel plate etc.This predeterminable area obtains rule for determine the size of target area image according to the size of the perforate on the steel plate.
Step S604 scans in target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule.Wherein, default scanning rule is for obtaining the image of a preliminary dimension from target area image.For example, read the binary data of expression target area image line by line, and the binary data that reads of buffer memory, when reaching preliminary dimension, the represented size of images of the binary data of buffer memory determines that the represented image of the binary data of buffer memory is a template image.
Step S606 judges whether the center pixel of each template image is desired value.For example, please be simultaneously referring to Fig. 2, template image 50 is of a size of n*n pixel size, and n=2x+1, x are natural number, n=5 in the present embodiment, the size of each pixel is 1bit, and each pixel has unique identifier DXY.With " 1 " expression, when being white, pixel represents when wherein pixel is for black with " 0 ".Can whether be that " 1 " judges whether the center pixel of template image 50 is black by the data of judging the D22 correspondence.
Step S608 when the center pixel of judging template image is desired value, obtains in each template image and the corresponding quantitative value with pixel of desired value of statistical rules according to statistical rules.This statistical rules is the number of the four limit black picture elements in each template image zone of statistics.For example, when the data of judging the D22 correspondence are " 1 ", then add up the quantity of black picture element among pixel D00, D01 on four limits of this template image 50, D02, D03, D04, D10, D14, D20, D24, D30, D34, D40, D41, D42, D43, the D44, for example, above-mentioned statistical can be: mode one, and pixel is the quantity of black among statistical pixel D00, D01, D02, D03, D04, D10, D14, D20, D24, D30, D34, D40, D41, D42, D43, the D44; Mode two, pixel is the quantity of black among statistical pixel D00, D01, D02, D10, D20, D30, D40, D41, the D42, pixel is the quantity of black among statistical pixel D00, D01, D02, D03, D04, D10, D14, D20, the D24 again, then pixel is the quantity of black among statistical pixel D02, D03, D04, D14, D24, D34, D42, D43, the D44, and pixel is the quantity of black among statistical pixel D20, D24, D30, D34, D40, D41, D42, D43, the D44 then.
Step S610 judges whether the quantitative value of the pixel with desired value is not more than preset reference value.For example, quantitative value and preset reference value that employing mode one is obtained compare, and judge with the 50 pairing perforates of this template image whether have burr with this; Perhaps, four quantitative values that employing mode two is counted out compare, and finding out four maximums in the quantitative value, and maximum and the preset reference value that finds out are compared.Judge with the 50 pairing perforates of this template image whether have burr with this.
Step S612 when the quantitative value of judging the pixel with desired value is not more than preset reference value, judges that the perforate corresponding with this template image has burr, and the output information.This information can show by LCDs, for testing staff's reference.
By above-mentioned burr detection device and burr detection method, processing module 22 scans in target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule, and when the center pixel of judging template image is black, obtain in this template image and the corresponding black picture element quantitative value of statistical rules according to statistical rules, and judge that when judging the black picture element quantitative value and be not more than preset reference value the perforate corresponding with this template image has burr, and the output information is to output module.So, burr detection device does not need artificial participation just can finish burr detecting operation to perforate on the steel plate automatically, has reduced testing staff's workload, helps modernized pipelining.
Claims (11)
1. burr detection device, it is characterized in that: this burr detection device comprises processing module and output module, this processing module is used for scanning in the target area image that prestores according to default scanning rule, to obtain and the corresponding template image of default scanning rule, and when the center pixel of judging template image is desired value, obtain in this template image and the corresponding quantitative value of statistical rules according to statistical rules with pixel of desired value, and judge that when the quantitative value of judging the pixel with desired value is not more than preset reference value the perforate corresponding with this template image has burr, and the output information is given output module; Output module is used for information is exported.
2. burr detection device as claimed in claim 1 is characterized in that: this default scanning rule is for obtaining the image of a preliminary dimension from target area image; This statistical rules has the number of the pixel of desired value for four limits of each template image of statistics; Desired value is used for the color of representing that the perforate burr is had.
3. burr detection device as claimed in claim 1, it is characterized in that: this burr detection device also comprises image collection module, and coordinate and predeterminable area that image collection module is used for describing according to being used for of filing in advance the steel plate position of opening obtain rule picked-up target area image; This predeterminable area obtains rule for determine the size of target area image according to the size of the perforate on the steel plate.
4. burr detection device as claimed in claim 1, it is characterized in that: desired value is a black, this processing module comprises central processing unit and memory, this memory is used to store burr trace routine and target area image, and this central processing unit produces following functional unit after this burr trace routine of operation:
Acquiring unit is used for according to default scanning rule target area image being scanned, to obtain and the corresponding template image of default scanning rule;
First comparing unit is used to judge whether the center pixel of template image is black, and when the center pixel of judging template image is black, produces first comparison signal, and sends first comparison signal to statistic unit;
Statistic unit is used to respond first comparison signal, obtains in each template image and the corresponding black picture element quantitative value of statistical rules according to statistical rules, and the black picture element quantitative value that statistic unit also obtains statistics offers second comparing unit;
Second comparing unit is used to judge whether the black picture element quantitative value is not more than preset reference value, and produces second comparison signal when black picture element quantitative value is not more than preset reference value judging, and second comparison signal is offered output unit;
Output unit is used for producing information according to second comparison signal, and sends the information that produces to output module.
5. burr detection device as claimed in claim 1 is characterized in that: desired value is a black, and this processing module comprises the field programmable gate array after memory, the programming;
This memory is used to store target area image;
Field programmable gate array after this programming produces corresponding circuit to realize the burr measuring ability, and this processing module comprises position generative circuit, data converting circuit, time-delay sample circuit, decision circuitry, computing circuit, comparison circuit and output circuit;
The position generative circuit is used for according to the coordinate generation corresponding address data that are used for describing the steel plate position of opening of filing in advance, and address date is offered memory;
Data converting circuit is used for the address date that reception memorizer response position generative circuit provides and the target area image data of exporting, and the target area image data that receive are carried out the data gray scale handle, obtaining corresponding binary data, and the binary data that obtains is offered the time-delay sample circuit;
The time-delay sample circuit is used to receive binary data and the buffer memory that data converting circuit provides, when the binary data of buffer memory reached the size of template image, time-delay sample circuit contribute is buffer memory to be offered decision circuitry and the pairing binary data of pixel on buffer memory and four limits template image is offered computing circuit with the pairing binary data of center pixel template image;
Decision circuitry is used for judging with the pairing binary data of center pixel template image whether the center pixel of template image is black according to that receive, and output judges that signal is to computing circuit when judging center pixel for black;
Computing circuit is used for response and judges signal, calculates the quantitative value of black picture element on four limits of template image according to the pairing binary data of pixel on that receive and four limits template image, and the quantitative value that calculates is offered comparison circuit;
Quantitative value and preset reference value that comparison circuit is used for receiving compare, and produce comparison signal when the quantitative value that compares reception is not more than preset reference value, and comparison signal is offered output circuit;
Output circuit is used for producing information according to comparison signal, and sends the information that produces to output module.
6. burr detection device as claimed in claim 1 is characterized in that: this template image is of a size of n*n pixel size, and n=2x+1, x are natural number.
7. burr detection method, this method comprises the steps:
Scan in default target area image according to default scanning rule, to obtain and the corresponding template image of default scanning rule;
Whether the center pixel of judging template image is desired value;
When the center pixel of judging template image is desired value, obtain in each template image and the corresponding quantitative value of statistical rules with pixel of desired value according to statistical rules;
Whether the quantitative value of judging the pixel with desired value is not more than preset reference value;
When being not more than preset reference value, the quantitative value of judging the pixel with desired value judges that the perforate corresponding with this template image has burr, and the output information.
8. burr detection method as claimed in claim 7 is characterized in that: this default scanning rule is for obtaining the image of a preliminary dimension from target area image; This statistical rules has the number of the pixel of desired value for four limits of each template image of statistics; Desired value is used for the color of representing that the perforate burr is had.
9. burr detection method as claimed in claim 7 is characterized in that: further comprising the steps of:
Coordinate and the predeterminable area of describing the steel mesh position of opening according to being used in filing in advance obtain rule picked-up target area image; Wherein, this predeterminable area obtains rule for determine the size of target area image according to the size of the perforate on the steel plate.
10. burr detection method as claimed in claim 7, it is characterized in that: desired value is a black, this template image is of a size of 5*5 pixel size, the size of each pixel is 1bit, represent with " 1 " when wherein pixel is for black, represent with " 0 " when pixel is white, and each pixel has unique identifier;
Whether the center pixel of judging template image is that the concrete steps of black are:
Obtain the pairing data of identifier of template image center pixel;
Judge whether the data of obtaining are " 1 ";
When judging the data obtained for " 1 ", the center pixel of determining template image is a black.
11. burr detection method as claimed in claim 10 is characterized in that: when the center pixel of judging template image is black, obtain in each template image with the concrete steps of the corresponding black picture element quantitative value of statistical rules according to statistical rules be:
Obtain the pairing data of identifier of pixel on template image four limits;
Statistics is the number of the identifier of " 1 ", and produces corresponding black picture element quantitative value.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010133482.XA CN102202142B (en) | 2010-03-26 | 2010-03-26 | Burr detection device and burr detection method |
| US13/031,577 US8605986B2 (en) | 2010-03-26 | 2011-02-21 | Burr detecting apparatus and burr detection method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201010133482.XA CN102202142B (en) | 2010-03-26 | 2010-03-26 | Burr detection device and burr detection method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102202142A true CN102202142A (en) | 2011-09-28 |
| CN102202142B CN102202142B (en) | 2014-04-30 |
Family
ID=44656546
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201010133482.XA Expired - Fee Related CN102202142B (en) | 2010-03-26 | 2010-03-26 | Burr detection device and burr detection method |
Country Status (2)
| Country | Link |
|---|---|
| US (1) | US8605986B2 (en) |
| CN (1) | CN102202142B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104933705A (en) * | 2015-05-29 | 2015-09-23 | 广东正业科技股份有限公司 | Slot hole detection method through time-space ring data structure and device thereof |
| CN109387178A (en) * | 2017-08-10 | 2019-02-26 | 波音公司 | Burr detection system and method |
| CN110987959A (en) * | 2019-12-16 | 2020-04-10 | 广州量子激光智能装备有限公司 | Online burr detection method |
| CN114998313A (en) * | 2022-07-18 | 2022-09-02 | 山东海鑫达石油机械有限公司 | Fluid conveying pipe orifice burr identification and positioning method based on visual positioning |
| CN115122691A (en) * | 2022-06-29 | 2022-09-30 | 江阴旺达商务贴有限公司 | System and method for manufacturing plastic conveyor belt body |
| CN115839663A (en) * | 2023-02-17 | 2023-03-24 | 肥城新查庄地质勘查有限公司 | Drilling accuracy detection tool and detection method |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6140042B2 (en) * | 2013-09-25 | 2017-05-31 | 株式会社総合車両製作所 | Evaluation method of friction stir welding |
| CN106781521B (en) * | 2016-12-30 | 2020-12-25 | 东软集团股份有限公司 | Traffic signal lamp identification method and device |
| CN114742826B (en) * | 2022-06-09 | 2022-09-02 | 深圳市智尚世家科技有限公司 | Production abnormity monitoring method for municipal clothing cleaning device |
| CN115880289B (en) * | 2023-02-21 | 2023-05-26 | 深圳普菲特信息科技股份有限公司 | Steel coil burr identification method, system and medium based on big data processing |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5485532A (en) * | 1991-09-27 | 1996-01-16 | Omron Corporation | Image processing device and method thereof |
| CN1798338A (en) * | 2004-12-30 | 2006-07-05 | 中兴通讯股份有限公司 | Method for segmenting mobile in video sequence |
| CN101145198A (en) * | 2007-09-21 | 2008-03-19 | 清华大学 | Certainty coding method and system in fingerprint identification |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3387499B2 (en) * | 1991-10-02 | 2003-03-17 | 富士通株式会社 | Orientation determination method in local region of contour line and determination method of line segment and angle |
-
2010
- 2010-03-26 CN CN201010133482.XA patent/CN102202142B/en not_active Expired - Fee Related
-
2011
- 2011-02-21 US US13/031,577 patent/US8605986B2/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5485532A (en) * | 1991-09-27 | 1996-01-16 | Omron Corporation | Image processing device and method thereof |
| CN1798338A (en) * | 2004-12-30 | 2006-07-05 | 中兴通讯股份有限公司 | Method for segmenting mobile in video sequence |
| CN101145198A (en) * | 2007-09-21 | 2008-03-19 | 清华大学 | Certainty coding method and system in fingerprint identification |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104933705A (en) * | 2015-05-29 | 2015-09-23 | 广东正业科技股份有限公司 | Slot hole detection method through time-space ring data structure and device thereof |
| CN104933705B (en) * | 2015-05-29 | 2018-07-06 | 南昌正业科技有限公司 | A kind of space-time loop data structure carries out the method and device of slot detection |
| CN109387178A (en) * | 2017-08-10 | 2019-02-26 | 波音公司 | Burr detection system and method |
| CN110987959A (en) * | 2019-12-16 | 2020-04-10 | 广州量子激光智能装备有限公司 | Online burr detection method |
| CN115122691A (en) * | 2022-06-29 | 2022-09-30 | 江阴旺达商务贴有限公司 | System and method for manufacturing plastic conveyor belt body |
| CN114998313A (en) * | 2022-07-18 | 2022-09-02 | 山东海鑫达石油机械有限公司 | Fluid conveying pipe orifice burr identification and positioning method based on visual positioning |
| CN115839663A (en) * | 2023-02-17 | 2023-03-24 | 肥城新查庄地质勘查有限公司 | Drilling accuracy detection tool and detection method |
Also Published As
| Publication number | Publication date |
|---|---|
| US20110235896A1 (en) | 2011-09-29 |
| US8605986B2 (en) | 2013-12-10 |
| CN102202142B (en) | 2014-04-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102202142B (en) | Burr detection device and burr detection method | |
| CN109100370A (en) | A kind of pcb board defect inspection method based on sciagraphy and connected domain analysis | |
| CN110830795B (en) | Image sensor dead pixel detection method and device and electronic equipment | |
| CN113763355A (en) | Defect detection method and device, electronic equipment and storage medium | |
| CN113706495B (en) | Machine vision detection system for automatically detecting lithium battery parameters on conveyor belt | |
| CN110473165A (en) | A kind of welding quality of circuit board detection method and device | |
| CN112053318A (en) | Two-dimensional PCB defect real-time automatic detection and classification device based on deep learning | |
| CN109889820A (en) | Detection method, device, storage medium and the terminal of binocular camera mould group | |
| CN102213586B (en) | Bad hole detection device and bad hole detection method | |
| CN114047123B (en) | Method and system for detecting production defects of integrated board | |
| CN109765240B (en) | Device and method for detecting stitch defects of industrial parts | |
| CN101303226A (en) | Method for measuring circuit board line width based on largest communication domain | |
| CN109444172A (en) | A kind of automatic optical detection device and its method suitable for artificial intelligence detection PCB | |
| CN109785294A (en) | A kind of pcb board defective locations detection system and method | |
| CN111861980B (en) | Imaging detection method, electronic equipment and computer readable storage medium | |
| CN112651966A (en) | Printed circuit board micro-defect detection method based on ACYOLOV4_ CSP | |
| CN102954760A (en) | Image measurement apparatus and image measurement method | |
| CN116109635A (en) | Method, device, equipment and medium for detecting surface quality of composite suspension insulator | |
| CN103913150B (en) | Intelligent electric energy meter electronic devices and components consistency detecting method | |
| CN112561875A (en) | Photovoltaic cell panel coarse grid detection method based on artificial intelligence | |
| CN116580026B (en) | Automatic optical detection method, equipment and storage medium for appearance defects of precision parts | |
| CN102856214A (en) | Circuit board mounting method | |
| CN116993654A (en) | Camera module defect detection method, device, equipment, storage medium and product | |
| CN115479891A (en) | Automatic detection system and method for circuit board mounted components based on image recognition | |
| CN209215256U (en) | A kind of automatic optical detection device suitable for artificial intelligence detection PCB |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20140430 Termination date: 20180326 |